@inproceedings{kepler-etal-2019-openkiwi,
title = "{O}pen{K}iwi: An Open Source Framework for Quality Estimation",
author = "Kepler, Fabio and
Tr{\'e}nous, Jonay and
Treviso, Marcos and
Vera, Miguel and
Martins, Andr{\'e} F. T.",
editor = "Costa-juss{\`a}, Marta R. and
Alfonseca, Enrique",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-3020",
doi = "10.18653/v1/P19-3020",
pages = "117--122",
abstract = "We introduce OpenKiwi, a Pytorch-based open source framework for translation quality estimation. OpenKiwi supports training and testing of word-level and sentence-level quality estimation systems, implementing the winning systems of the WMT 2015{--}18 quality estimation campaigns. We benchmark OpenKiwi on two datasets from WMT 2018 (English-German SMT and NMT), yielding state-of-the-art performance on the word-level tasks and near state-of-the-art in the sentence-level tasks.",
}
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%0 Conference Proceedings
%T OpenKiwi: An Open Source Framework for Quality Estimation
%A Kepler, Fabio
%A Trénous, Jonay
%A Treviso, Marcos
%A Vera, Miguel
%A Martins, André F. T.
%Y Costa-jussà, Marta R.
%Y Alfonseca, Enrique
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F kepler-etal-2019-openkiwi
%X We introduce OpenKiwi, a Pytorch-based open source framework for translation quality estimation. OpenKiwi supports training and testing of word-level and sentence-level quality estimation systems, implementing the winning systems of the WMT 2015–18 quality estimation campaigns. We benchmark OpenKiwi on two datasets from WMT 2018 (English-German SMT and NMT), yielding state-of-the-art performance on the word-level tasks and near state-of-the-art in the sentence-level tasks.
%R 10.18653/v1/P19-3020
%U https://aclanthology.org/P19-3020
%U https://doi.org/10.18653/v1/P19-3020
%P 117-122
Markdown (Informal)
[OpenKiwi: An Open Source Framework for Quality Estimation](https://aclanthology.org/P19-3020) (Kepler et al., ACL 2019)
ACL
- Fabio Kepler, Jonay Trénous, Marcos Treviso, Miguel Vera, and André F. T. Martins. 2019. OpenKiwi: An Open Source Framework for Quality Estimation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 117–122, Florence, Italy. Association for Computational Linguistics.